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AI architecture is a crucial factor in developing high-quality AI applications. Software engineering complements AI, particularly through RAG architecture, and an AI-first mindset combined with a robust architecture is essential for business success.

Understanding and acting on tabular data, such as CRM and ERP exports, SQL databases, Excel sheets and comma separated values, remains challenging for large language models. In this post we show how an agentic workflow can take on the challenge of understanding tabulated data.